Semi-automated construction of patient individualised clinical target volumes for radiotherapy treatment of glioblastoma utilising diffusion tensor decomposition maps.

OBJECTIVES: Glioblastoma multiforme (GBM) is a highly infiltrative primary brain tumour with an aggressive clinical course. Diffusion tensor imaging (DT-MRI or DTI) is a recently developed technique capable of visualising subclinical tumour spread into adjacent brain tissue. Tensor decomposition through p and q maps can be used for planning of treatment. Our objective was to develop a tool to automate the segmentation of DTI decomposed p and q maps in GBM patients in order to inform construction of radiotherapy target volumes. METHODS: Chan-Vese level set model is applied to segment the p map using the q map as its initial starting point. The reason of choosing this model is because of the robustness of this model on either conventional MRI or only DTI. The method was applied on a data set consisting of 50 patients having their gross tumour volume delineated on their q map and Chan-Vese level set model uses these superimposed masks to incorporate the infiltrative edges. RESULTS: The expansion of tumour boundary from q map to p map is clearly visible in all cases and the Dice coefficient (DC) showed a mean similarity of 74% across all 50 patients between the manually segmented ground truth p map and the level set automatic segmentation. CONCLUSION: Automated segmentation of the tumour infiltration boundary using DTI and tensor decomposition is possible using Chan-Vese level set methods to expand q map to p map. We have provided initial validation of this technique against manual contours performed by experienced clinicians. ADVANCES IN KNOWLEDGE: This novel automated technique to generate p maps has the potential to individualise radiation treatment volumes and act as a decision support tool for the treating oncologist.This study was funded by an NIHR Clinician Scientist Fellowship for a SJP, project reference NIHR/CS/009/011. The research was supported by the NIHR Brain Injury MedTech Co-operative based at Cambridge University Hospitals NHS Foundation Trust and University of Cambridge and the NIHR Cambridge BRC. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Also, RR is supported as part of the CRUK-funded PRaM-GBM study (C9216/A19732). NVIDIA Corporation is gratefully acknowledged for the donation of two Titan X GPUs for our research

Memory recovery in relation to default mode network impairment and neurite density during brain tumor treatment.

OBJECTIVE: The aim of this study was to test brain tumor interactions with brain networks, thereby identifying protective features and risk factors for memory recovery after resection. METHODS: Seventeen patients with diffuse nonenhancing glioma (ages 22-56 years) underwent longitudinal MRI before and after surgery, and during a 12-month recovery period (47 MRI scans in total after exclusion). After each scanning session, a battery of memory tests was performed using a tablet-based screening tool, including free verbal memory, overall verbal memory, episodic memory, orientation, forward digit span, and backward digit span. Using structural MRI and neurite orientation dispersion and density imaging (NODDI) derived from diffusion-weighted images, the authors estimated lesion overlap and neurite density, respectively, with brain networks derived from normative data in healthy participants (somatomotor, dorsal attention, ventral attention, frontoparietal, and default mode network [DMN]). Linear mixed-effect models (LMMs) that regressed out the effect of age, gender, tumor grade, type of treatment, total lesion volume, and total neurite density were used to test the potential longitudinal associations between imaging markers and memory recovery. RESULTS: Memory recovery was not significantly associated with either the tumor location based on traditional lobe classification or the type of treatment received by patients (i.e., surgery alone or surgery with adjuvant chemoradiotherapy). Nonlocal effects of tumors were evident on neurite density, which was reduced not only within the tumor but also beyond the tumor boundary. In contrast, high preoperative neurite density outside the tumor but within the DMN was associated with better memory recovery (LMM, p value after false discovery rate correction [Pfdr] < 10-3). Furthermore, postoperative and follow-up neurite density within the DMN and frontoparietal network were also associated with memory recovery (LMM, Pfdr = 0.014 and Pfdr = 0.001, respectively). Preoperative tumor and postoperative lesion overlap with the DMN showed a significant negative association with memory recovery (LMM, Pfdr = 0.002 and Pfdr < 10-4, respectively). CONCLUSIONS: Imaging biomarkers of cognitive recovery and decline can be identified using NODDI and resting-state networks. Brain tumors and their corresponding treatment affecting brain networks that are fundamental for memory functioning such as the DMN can have a major impact on patients' memory recovery.We thank all patients for generous involvement in the study. We also thank to Luca Villa, Jessica Ingham, Alexa Mcdonald for their contribution to the study. This research was supported by The Brain Tumour Charity and the Guarantors of Brai

Local alkylating chemotherapy applied immediately after 5-ALA guided resection of glioblastoma does not provide additional benefit.

Grade IV glioma is the most common and aggressive primary brain tumour. Gross total resection with 5-aminolevulinic acid (5-ALA) guided surgery combined with local chemotherapy (carmustine wafers) is an attractive treatment strategy in these patients. No previous studies have examined the benefit carmustine wafers in a treatment programme of 5-ALA guided resection followed by a temozolomide-based chemoradiotherapy protocol. The objective of this study was to examine the benefit of carmustine wafers on survival in patients undergoing 5-ALA guided resection. A retrospective cohort study of 260 patients who underwent 5-ALA resection of confirmed WHO 2007 Grade IV glioma between July 2009 and December 2014. Survival curves were calculated using the Kaplan-Meier method from surgery. The log-rank test was used to compare survival curves between groups. Cox regression was performed to identify variables predicting survival. A propensity score matched analysis was used to compare survival between patients who did and did not receive carmustine wafers while controlling for baseline characteristics. Propensity matched analysis showed no significant survival benefit of insertion of carmustine wafers over 5-ALA resection alone (HR 0.97 [0.68-1.26], p = 0.836). There was a trend to higher incidence of wound infection in those who received carmustine wafers (15.4 vs. 7.1%, p = 0.064). The Cox regression analysis showed that intraoperative residual fluorescent tumour and residual enhancing tumour on post-operative MRI were significantly predictive of reduced survival. Carmustine wafers have no added benefit following 5-ALA guided resection. Residual fluorescence and residual enhancing disease following resection have a negative impact on survival

An Investigation of Cognitive Deficits Related to Surgery for Glioblastoma using a Computerised Assessment Tool

Thesis Abstract An Investigation of Cognitive Deficits Related to Surgery for Glioblastoma using a Computerised Assessment Tool - Rohitashwa Sinha Glioblastoma, the most aggressive type of primary brain cancer, causes abysmal survival rates and high risks of cognitive deficit to its sufferers. These deficits are due to both its being diffusely infiltrative and its radical treatments such as brain surgery and radiotherapy. Currently the course of cognitive deficits from before to after surgery has not been reliably researched. Studies report high rates of drop-out due to burdensome ‘pen-and-paper’ based assessments conducted by neuropsychologists, a lack of these resources entirely or the data collection being focused on the period around radiotherapy or less aggressive tumours instead. As a result, patients still undergo resection surgery for glioblastoma without a reliable evidence base for making their treatment decisions, without any assessment for their cognitive deficit burden and without any targeted interventions to protect their cognitive function. In this doctoral research, I have set up a prospective study to assess cognitive function before and after resection surgery, but before radiotherapy and with particular focus on participants with glioblastoma who have been underserved by current infrastructure and research focus. The methodology involves using a computerised testing battery called ‘OCS-Bridge’, which has broadened the access to such cognitive assessments. Participant retention has been higher than in the literature. This may be due in part to the efficiency of the format as well as the study design for data collection, where assessment timepoints were advised by patients and carers rather than clinicians. Using a variety of analysis techniques, this thesis progresses through a systematic review confirming the lack of reliable consensus in this area and a format comparison study to support the use of OCS-Bridge by comparison to conventional testing. Next, machine learning and Kaplan-Meier analyses are used to show cognitive deficits as predictors of clinical outcomes including overall survival. The longitudinal analyses of the high peri-operative odds of cognitive deficits until radiotherapy follows. Finally, a tract based spatial statistics study using diffusion tensor MRI brain scans demonstrates that a common anatomical mechanism exists, affecting the same right hemisphere white matter tracts underlying social cognition deficits in participants with glioblastoma as is seen in traumatic brain injury and neurodegenerative disease contexts. 3 By contributing new knowledge, research methodology, immediately translational implications for clinical practice and by linking the mechanisms of cognitive deficits between glioblastoma and other neurological diseases, the results herein have already secured further research funding. This future work will build on the understanding of cognitive deficits presented here and to trial a targeted rehabilitation intervention to help people with glioblastoma and their families.Royal College of Surgeons of England Cancer Research U

Glioblastoma surgery related emotion recognition deficits are associated with right cerebral hemisphere tract changes

Patients with glioblastoma face abysmal overall survival, cognitive deficits, poor quality of life and limitations to social participation; partly attributable to surgery. Emotion recognition deficits mediated by pathophysiological mechanisms in the right inferior fronto-occipital fasciculus and right inferior longitudinal fasciculus have been demonstrated in traumatic brain injury and dementia, with negative associations for social participation. We hypothesise similar mechanisms occur in patients undergoing resection surgery for glioblastoma. Here, we apply tract-based spatial statistics using a combination of automated image registration methods alongside cognitive testing before and after surgery. In this prospective, longitudinal, observational study of 15 patients, surgery is associated with an increase of emotion recognition deficits (p=0.009) and this is correlated with decreases in fractional anisotropy in the Inferior Longitudinal Fasciculus, Inferior Fronto-Occipital Fasciculus, Anterior Thalamic Radiation and Uncinate Fasciculus; all in the right hemisphere (p=0.014). Methodologically, the combination of registration steps used demonstrate that tract-based spatial statistics can be applied in the context of large, scan distorting lesions such as glioblastoma. These results can inform clinical consultations with patients undergoing surgery, support consideration for social cognition rehabilitation and are consistent with theoretical mechanisms that implicate these tracts in emotion recognition deficits across different diseases.CRUK, NIHR and MRC have funded the authors of this pape

Characterizing tumor invasiveness of glioblastoma using multiparametric magnetic resonance imaging.

OBJECTIVE: The objective of this study was to characterize the abnormalities revealed by diffusion tensor imaging (DTI) using MR spectroscopy (MRS) and perfusion imaging, and to evaluate the prognostic value of a proposed quantitative measure of tumor invasiveness by combining contrast-enhancing (CE) and DTI abnormalities in patients with glioblastoma. METHODS: Eighty-four patients with glioblastoma were recruited preoperatively. DTI was decomposed into isotropic (p) and anisotropic (q) components. The relative cerebral blood volume (rCBV) was calculated from the dynamic susceptibility contrast imaging. Values of N-acetylaspartate, myoinositol, choline (Cho), lactate (Lac), and glutamate + glutamine (Glx) were measured from multivoxel MRS and normalized as ratios to creatine (Cr). Tumor regions of interest (ROIs) were manually segmented from the CE T1-weighted (CE-ROI) and DTI-q (q-ROI) maps. Perfusion and metabolic characteristics of these ROIs were measured and compared. The relative invasiveness coefficient (RIC) was calculated as a ratio of the characteristic radii of CE-ROI and q-ROI. The prognostic significance of RIC was tested using Kaplan-Meier and multivariate Cox regression analyses. RESULTS: The Cho/Cr, Lac/Cr, and Glx/Cr in q-ROI were significantly higher than CE-ROI (p = 0.004, p = 0.005, and p = 0.007, respectively). CE-ROI had significantly higher rCBV values than q-ROI (p < 0.001). A higher RIC was associated with worse survival in a multivariate overall survival (OS) model (hazard ratio [HR] 1.40, 95% confidence interval [CI] 1.06-1.85, p = 0.016) and progression-free survival (PFS) model (HR 1.55, 95% CI 1.16-2.07, p = 0.003). An RIC cutoff value of 0.89 significantly predicted shorter OS (median 384 vs 605 days, p = 0.002) and PFS (median 244 vs 406 days, p = 0.001). CONCLUSIONS: DTI-q abnormalities displayed higher tumor load and hypoxic signatures compared with CE abnormalities, whereas CE regions potentially represented the tumor proliferation edge. Integrating the extents of invasion visualized by DTI-q and CE images into clinical practice may lead to improved treatment efficacy.The Cambridge Trust and China Scholarship Council ; Clare College; the British Neuro-Oncology Society; the EG Fearnsides Trust; the International Society for Magnetic Resonance in Medicin

A Prospective Study of Longitudinal Risks of Cognitive Deficit for People Undergoing Glioblastoma Surgery Using a Tablet Computer Cognition Testing Battery: Towards Personalized Understanding of Risks to Cognitive Function

Glioblastoma and the surgery to remove it pose high risks to the cognitive function of patients. Little reliable data exist about these risks, especially postoperatively before radiotherapy. We hypothesized that cognitive deficit risks detected before surgery will be exacerbated by surgery in patients with glioblastoma undergoing maximal treatment regimens. We used longitudinal electronic cognitive testing perioperatively to perform a prospective, longitudinal, observational study of 49 participants with glioblastoma undergoing surgery. Before surgery (A1), the participant risk of deficit in 5/6 cognitive domains was increased compared to normative data. Of these, the risks to Attention (OR = 31.19), Memory (OR = 97.38), and Perception (OR = 213.75) were markedly increased. These risks significantly increased in the early period after surgery (A2) when patients were discharged home or seen in the clinic to discuss histology results. For participants tested at 4&ndash;6 weeks after surgery (A3) before starting radiotherapy, there was evidence of risk reduction towards A1. The observed risks of cognitive deficit were independent of patient-specific, tumour-specific, and surgery-specific co-variates. These results reveal a timeframe of natural recovery in the first 4&ndash;6 weeks after surgery based on personalized deficit profiles for each participant. Future research in this period could investigate personalized rehabilitation tools to aid the recovery process found

A Prospective Study of Longitudinal Risks of Cognitive Deficit for People Undergoing Glioblastoma Surgery Using a Tablet Computer Cognition Testing Battery: Towards Personalized Understanding of Risks to Cognitive Function

Glioblastoma and the surgery to remove it pose high risks to the cognitive function of patients. Little reliable data exist about these risks, especially postoperatively before radiotherapy. We hypothesized that cognitive deficit risks detected before surgery will be exacerbated by surgery in patients with glioblastoma undergoing maximal treatment regimens. We used longitudinal electronic cognitive testing perioperatively to perform a prospective, longitudinal, observational study of 49 participants with glioblastoma undergoing surgery. Before surgery (A1), the participant risk of deficit in 5/6 cognitive domains was increased compared to normative data. Of these, the risks to Attention (OR = 31.19), Memory (OR = 97.38), and Perception (OR = 213.75) were markedly increased. These risks significantly increased in the early period after surgery (A2) when patients were discharged home or seen in the clinic to discuss histology results. For participants tested at 4–6 weeks after surgery (A3) before starting radiotherapy, there was evidence of risk reduction towards A1. The observed risks of cognitive deficit were independent of patient-specific, tumour-specific, and surgery-specific co-variates. These results reveal a timeframe of natural recovery in the first 4–6 weeks after surgery based on personalized deficit profiles for each participant. Future research in this period could investigate personalized rehabilitation tools to aid the recovery process found.Cancer Research UK (RRZB/040 and RRAG/287) Royal College of Surgeons of England (RRAG/093) Medical Research Council (SUAG/049 and G101-400); National Institute for Health Research (NIHR), Career Development Fellowship for this research project (CDF-2018-11-ST2-003)

Structural connectome quantifies tumour invasion and predicts survival in glioblastoma patients

Glioblastoma is characterized by diffuse infiltration into the surrounding tissue along white matter tracts. Identifying the invisible tumour invasion beyond focal lesion promises more effective treatment, which remains a significant challenge. It is increasingly accepted that glioblastoma could widely affect brain structure and function, and further lead to reorganization of neural connectivity. Quantifying neural connectivity in glioblastoma may provide a valuable tool for identifying tumour invasion. Here we propose an approach to systematically identify tumour invasion by quantifying the structural connectome in glioblastoma patients. We first recruit two independent prospective glioblastoma cohorts: the discovery cohort with 117 patients and validation cohort with 42 patients. Next, we use diffusion MRI of healthy subjects to construct tractography templates indicating white matter connection pathways between brain regions. Next, we construct fractional anisotropy skeletons from diffusion MRI using an improved voxel projection approach based on the tract-based spatial statistics, where the strengths of white matter connection and brain regions are estimated. To quantify the disrupted connectome, we calculate the deviation of the connectome strengths of patients from that of the age-matched healthy controls. We then categorize the disruption into regional disruptions on the basis of the relative location of connectome to focal lesions. We also characterize the topological properties of the patient connectome based on the graph theory. Finally, we investigate the clinical, cognitive and prognostic significance of connectome metrics using Pearson correlation test, mediation test and survival models. Our results show that the connectome disruptions in glioblastoma patients are widespread in the normal-appearing brain beyond focal lesions, associated with lower preoperative performance (P &lt; 0.001), impaired cognitive function (P &lt; 0.001) and worse survival (overall survival: hazard ratio = 1.46, P = 0.049; progression-free survival: hazard ratio = 1.49, P = 0.019). Additionally, these distant disruptions mediate the effect on topological alterations of the connectome (mediation effect: clustering coefficient -0.017, P &lt; 0.001, characteristic path length 0.17, P = 0.008). Further, the preserved connectome in the normal-appearing brain demonstrates evidence of connectivity reorganization, where the increased neural connectivity is associated with better overall survival (log-rank P = 0.005). In conclusion, our connectome approach could reveal and quantify the glioblastoma invasion distant from the focal lesion and invisible on the conventional MRI. The structural disruptions in the normal-appearing brain were associated with the topological alteration of the brain and could indicate treatment target. Our approach promises to aid more accurate patient stratification and more precise treatment planning